Skill UI

Store and query genomic variant data with TileDB sparse arrays. Ingest VCF/BCF files, add samples incrementally, run parallel region queries, and export subsets for population genomics workflows.

Generate data analysis reports by exploring database tables, running multidimensional SQL queries, performing deep attribution analysis, and outputting dynamic HTML visual reports with ECharts for business, trend, and KPI scenarios.

This skill leverages the Gemini AI model to perform comprehensive and broad literature discovery across academic domains. Unlike traditional APIs, it decomposes complex research queries into sub-problems, explores topic aliases, and surfaces highly relevant papers that might otherwise be missed. It is ideal for conducting deep, multi-angled literature reviews and achieving a holistic view of a research field.

This advanced skill acts as a hybrid router for complex research queries. It deterministically classifies the user's intent, delegating to specialized modules (e.g., funding grants, academic literature, patent search, company dossier) when applicable. If no specialist fits, it executes a robust fallback plan, synthesizing multi-source information into a detailed, cited briefing or document. Ideal for comprehensive investigative research across multiple domains.

Generates weekly telemetry reports and customer adoption reports for Azure Backup MCP tools. Runs KQL queries to classify errors into Customer/Azure Service/MCP Tool Bug, identifies customers via cross-cluster joins, compares week-over-week metrics, correlates with merged PRs, and produces an Outlook-compatible HTML report.

A unified CLI tool that queries multiple web and academic search engines (Crossref, Brave, Tavily, DuckDuckGo) in parallel. It aggregates results, extracting structured metadata like DOI, publication year, and authors. Ideal for deep research, cross-checking claims, or comparing scholarly coverage against general web results.

Provides expert guidance for connecting to Power BI Desktop's local tabular model using the Tabular Object Model (TOM) and ADOMD.NET via PowerShell. This skill covers model enumeration, executing DAX queries, metadata modification (tables, measures, relationships), query tracing, and model refreshing. It is specifically designed for managing the underlying data model structure when external tools like Tabular Editor CLI are unavailable.

Velociraptor is a powerful open-source platform for endpoint visibility and digital forensics. It allows users to deploy agents across thousands of endpoints and execute sophisticated VQL (Velociraptor Query Language) queries. This enables large-scale, on-demand forensic artifact collection, TTP hunting, and continuous monitoring during incident response, even on air-gapped or unmanaged systems.

This skill helps diagnose performance bottlenecks, slow jobs, and expensive queries across various data platforms (Airflow, dbt, Databricks). It uses a tiered investigation approach, starting with broad discovery to pinpoint problematic jobs or queries, bridging to affected tables, and finally drilling down to identify root causes, latency trends, and change-related regressions.

This skill allows users to extract structured data (text, tables, attributes) from rendered web pages. It enhances traditional web scraping by ensuring all extracted strings pass mandatory AIDefence PII checks and prompt-injection gates before being stored or returned to the model. It supports building reusable extraction templates and running one-shot queries.

This skill queries the NCATS Translator ARAX API for biomedical knowledge-graph relationships. It supports one-hop and two-hop lookups with Biolink constraints, entity normalization, and provider federation. Users can inspect provenance and edge bindings. It is designed for public research queries only, requiring Python 3.10+ and HTTPS access. Do not use for clinical guidance or sensitive data.